The 'svmtrain' function returns a model which can be used for future
prediction. It is a structure and is organized as [Parameters, nr_class,
totalSV, rho, Label, ProbA, ProbB, nSV, sv_coef, SVs]:
-Parameters: parameters
-nr_class: number of classes; = 2 for regression/one-class svm
-totalSV: total #SV
-rho: -b of the decision function(s) wx+b
-Label: label of each class; empty for regression/one-class SVM
-ProbA: pairwise probability information; empty if -b 0 or in one-class SVM
-ProbB: pairwise probability information; empty if -b 0 or in one-class SVM
-nSV: number of SVs for each class; empty for regression/one-class SVM
-sv_coef: coefficients for SVs in decision functions
-SVs: support vectors
相关文章：